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Tutorial - NanoSAM

Let's run NVIDIA's NanoSAM to check out the performance gain by distillation.

What you need

  1. One of the following Jetson:

    Jetson AGX Orin (64GB) Jetson AGX Orin (32GB) Jetson Orin NX (16GB) Jetson Orin Nano (8GB)

  2. Running one of the following versions of JetPack:

    JetPack 5 (L4T r35.x) JetPack 6 (L4T r36.x)

  3. Sufficient storage space (preferably with NVMe SSD).

    • 6.3GB for container image
    • Spaces for models

  4. Clone and setup jetson-containers:

    git clone https://github.com/dusty-nv/jetson-containers
bash jetson-containers/install.sh

How to start

Use the jetson-containers run and autotag commands to automatically pull or build a compatible container image.

jetson-containers run $(autotag nanosam)

Run examples

Inside the container, you can move to /opt/nanosam directory, to go through all the examples demonstrated on the repo.

cd /opt/nanosam

To run the "Example 1 - Segment with bounding box":

python3 examples/basic_usage.py \
    --image_encoder="data/resnet18_image_encoder.engine" \
    --mask_decoder="data/mobile_sam_mask_decoder.engine"

The result is saved under /opt/nanosam/data/basic_usage_out.jpg.

To check on your host machine, you can copy that into /data directory of the container where that is mounted from the host.

cp data/basic_usage_out.jpg /data/

Then you can go to your host system, and find the file under jetson-containers/data/basic_usage_out.jpg

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